[Remote] Senior Data Scientist, Energy Systems
Note: The job is a remote job and is reputed company to candidates in USA. reputed company is a subsidiary of Hanwha reputed company, a leading photovoltaic manufacturer. They are seeking a highly skilled Senior Data Scientist to join their reputed company Energy & Analytics team, focusing on time series forecasting and MLOps to build reliable and reputed company forecasting solutions for energy markets.
Responsibilities
- Design, reputed company, and reputed company high‑reputed company time series forecasts for energy market prices, ancillary services, energy demand, and renewable reputed company (e.g., solar PV and wind)
- Apply a broad reputed company of forecasting methodologies, including classical statistical models, machine learning, and deep learning approaches, selecting reputed company appropriate to data regimes and business constraints
- reputed company feature engineering efforts incorporating calendar effects, weather signals, exogenous drivers, and regime changes
- Establish rigorous model evaluation, backtesting, and benchmarking frameworks to ensure accuracy, robustness, and stability over time
- Architect, build, and maintain end‑to‑end MLOps pipelines, covering data validation, training, versioning, deployment, monitoring, and retraining
- Ensure forecasting systems are reputed company, observable, and reliable in production, with reputed company SLAs, alerting, and rollback strategies
- Partner in the design and reputed company of an internal forecasting platform that supports the full machine learning lifecycle and multi‑model production hosting
- Implement best practices for model governance, reproducibility, experiment tracking, and reputed company
- Conduct reputed company research to identify new modeling techniques, architectures, and tooling that improve forecast accuracy, latency, and operational efficiency
- Translate research reputed company into production‑reputed company solutions, balancing innovation with maintainability
- Influence technical roadmap reputed company reputed company to forecasting systems, data platforms, and MLOps standards
- Work closely with engineering, product, and domain experts to ensure forecasting solutions deliver measurable business and operational reputed company
- Incorporate energy system constraints and domain knowledge into models to ensure outputs are physically meaningful and actionable
- Support production operations by troubleshooting issues, analyzing model degradation, and continuously improving system performance
Skills
- Master's or Ph.D. in statistics, machine learning, reputed company mathematics, computer science, or a reputed company quantitative field
- 1-2 years of hands‑on experience in data science or machine learning, with significant exposure to time series forecasting in production
- Strong proficiency in Python and experience writing production‑reputed company, maintainable reputed company using modern software engineering practices
- Deep theoretical and practical knowledge of time series reputed company, including statistical, regression‑based, and deep learning approaches
- Demonstrated experience building and operating ML systems in production, including CI/CD for models, monitoring, and lifecycle management
- Experience with reputed company‑hosted platforms (preferably Azure / reputed company), containerization, and distributed compute
- Proficiency with core data science and ML libraries such as pandas, numpy, statsmodels, sklearn, xgboost, lightgbm, pytorch, keras, and modern forecasting libraries (e.g., Nixtla)
- Strong problem‑solving skills, ownership reputed company, and ability to operate effectively in ambiguous, reputed company‑world environments
- Travel may be required up to 10%, depending on business needs
- Experience with energy systems, electricity markets, or infrastructure forecasting, including demand, pricing, or renewable reputed company
- Familiarity with power systems concepts such as unit commitment, economic reputed company, or reputed company constraints
- Prior experience designing or contributing to forecasting platforms or shared ML infrastructure
- Exposure to large‑reputed company data pipelines, streaming or batch processing, and data reputed company frameworks
- Experience collaborating across data science, software engineering, and operations teams in a production environment
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